Context-Sensitive Support Levels

Definition

Context-Sensitive Support Levels examines the mechanisms, conditions and outcomes through which this factor shapes human cognition, learning, collaboration or sustainable performance in AI-supported settings.

Why this matters

Context-Sensitive Support Levels may materially affect human capability, independence, confidence, safety and productivity. Poorly designed assistance can create hidden costs even where short-term output appears to improve.

Research questions

How should assistance vary across task stakes, complexity, privacy and user expertise?

Hypotheses

Context models that include consequence and reversibility will calibrate support better than complexity-only models.

Proposed methods

multi-arm assistance-level experiments; longitudinal usage analysis; skill-retention tests; preference elicitation; A/B testing; pre-registered analysis; active comparison; subgroup and accessibility analysis; delayed retention or longitudinal follow-up; adverse-effect capture; reproducibility testing; participant debrief

Stakeholders and beneficiaries

end users; UX researchers; AI developers; product managers; safety teams; employers; regulators; Context-Sensitive Support Levels domain specialists; affected user advisory panel